Many methods and systems are known for deriving three-dimensional (‘3D’) information from a plurality of two-dimensional (‘2D’) image frames, for instance photographs. H. Bay, T. Tuytelaars and L. Van Gool (Speeded Up Robust Features, Proceedings of the Ninth European Conference on Computer Vision, 2006) and Lowe (Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, 2:91-110, 2004) teach respective techniques for extracting sets of 2D features from image frames and matching sets respectively extracted from successive frames, such that each pair of matched features refers to a same 3D point in a scene captured in the image frames.
A more widespread use of these methods in image processing applications referred to as ‘augmented reality’ applications, the purpose of which is to embed, impart or map additional information to 2D image data captured in real-time by imaging means, remains impeded by the amount of data processing resources required for accurately extracting 3D data from 2D image data.
The constant growth of air travel over the past decades has resulted both in larger aircrafts being constantly developed for carrying ever more passengers and cargo, recently resulting in such large airliners as the Airbus A380, Boeing 747-8 and Antonov An225, and in ever-increasing congestion on airport ramps and taxiways for aircrafts of all sizes. There has been a corresponding increase in flight support traffic and other airport features moving adjacent aircrafts, miscellaneously comprising fuel tenders, mobile stairs, articulated jet bridges, servicing trolleys, luggage trains and more.
Despite the pace and extent of aircraft technical developments, ground manoeuvring for aircraft remains essentially reliant on visual observation by the pilot crew, whose situational awareness may at times be impeded by a sensory overload resulting from a busy ground environment. The combination of the above factors has contributed, and continues to contribute, to an increase in ground collisions, at an annual cost last estimated at $11 bn in 2007.
Many modern aircrafts now include what is known as a “glass cockpit”, a flight navigation data processing system which relays environmental information gathered in real time by a multitude of onboard sensors such as a Global Positioning System, laser range finder, ground radar, odometer, Inertial Measurement Unit and more to the pilot crew via multifunctional digital instrument displays. This advanced feature remains a sub-optimal solution for mitigating the ground manoeuvring risks described above, even when the aircraft includes a real-time 2D video or digital image frame feed to the crew from one or more cameras located about the aircraft, since the 2D image data on a relevant instrument display lacks distance information, which other onboard sensors may yet relay, but in a visually counter-intuitive or dissociative form on a different instrument display, or an alternative user interface if the same instrument display must be used.
It would therefore be advantageous to provide an improved method and system, in which the processing of image data for the estimation of camera motion and the recovery of a 3D scene structure from a plurality of image frames requires comparatively less data processing resources relative to known solutions.
It would also be advantageous to provide such a system to assist the situational awareness of vehicle operators, particularly aircraft pilots, during manoeuvring in densely-populated and/or fast-changing environments.